The subject matter disclosed herein relates to the identification and analysis of geologic faults in seismic data.
Seismic data is collected and used for identifying and evaluating subsurface structures and layers within the earth. In practice, the seismic data is derived based on the propagation of seismic waves through the various geologic strata. In particular, the propagation of seismic waves may be useful in localizing the various edges and boundaries associated with different strata or layers within the earth and with the surfaces of various formations or structures that may be present underground.
The seismic waves used to generate seismic data may be created using any number of mechanisms, including explosives, air guns, or other mechanisms capable of creating vibrations or seismic waves capable of spreading through the Earth's subsurface. The seismic waves may reflect, to various degrees, at the boundaries or transitions between strata or structures, and these reflected seismic waves are detected and suitably processed to form a set of seismic data that may be used to examine the subsurface area being investigated.
Geologic faults may be observed within the various layers identified in a set of seismic data. Such faults are discontinuations of seismic horizons observed in the data. The fault data may be useful in searching for mineral resources, such as hydrocarbons. In particular, the faults can serve as trapping configurations for hydrocarbons and, thus, may indicate where concentrations of hydrocarbons can be found. One challenge that arises in the context of the analysis of fault data is that the stratigraphic surfaces on two sides of the fault may need to be matched to link seismic reflectors across the faults. This linkage may be useful in applications like well ties or stratigraphic interpretation. Further, in production contexts, analyzing hydrocarbon sealing and transmission mechanisms across the faults may be useful in reservoir management and drill planning.
Conventional approaches for fault interpretation and analysis, however, suffer from various inefficiencies and deficiencies and, in particular, may utilize significant levels of user involvement, and thus may be labor intensive. For example, existing fault interpretation of seismic data may rely heavily on having users interpret numerous 2D slices. Based on how horizons on each side match, an interpreter may make multiple hypotheses that have to be validated in the 3D volume set for a consistent interpretation. Since an inconsistent hypothesis may lead to discarding the interpretation, and starting over, existing manual interpretation approaches are inefficient.